遗传算法及其在速度结构与震源联合反演中的应用

遗传算法是近年来发展较快的一种求解多参数非线性优化问题的有效方法。本文通过对遗传传算法的介绍。对该方法的发展现状及特点进行了分析，在此基础上，对遗传算法进行了改进：通过引入放大系统Ｋ。对目标函数进行压缩及扩展来提高遗传算法的搜索机制；

GENETIC ALGORITHMS AND ITS APPLICATION TO THE SIMULTANEOUS INVERSION FOR VELOCITY STRUCTURE AND FOCUS

Genetic algorithm is a rapid developmental method, which can solve nonlinear multi parameters optimization in recent years. In this paper, by a detailed introduction, the present situation and characteristic of the method is analyzed. Base on this, genetic algorithm is improved. By introduced an amplified parameter, K, objection function can be compressed and amplified in order to improve the search mechanism. In crossover, by introduced the elite selection, the principle of 'survival of the best' is reflected. Modified genetic algorithm combines parallel genetic algorithms with dynamic adjust of the range of the parameters. At last, the valid of the method is qualified by the example of the simultaneous inversion for velocity structure and focus.